Measuring semantic similarity based on weighting attributes of edge counting

Ju Hum Kwon, Chang Joo Moon, Soo Hyun Park, Doo Kwon Baik

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

Semantic similarity measurement can be applied in many different fields and has variety of ways to measure it. As a foundation paper for semantic similarity, we explored the edge counting method for measuring semantic similarity by considering the weighting attributes from where they affect an edge's strength. We considered the attributes of scaling depth effect and semantic relation type extensively. Further, we showed how the existing edge counting method could be improved by considering virtual connection. Finally, we compared the performance of the proposed method with a benchmark set of human judgment of similarity. The results of proposed measure were encouraging compared with other combined approaches.

Original languageEnglish
Pages (from-to)470-480
Number of pages11
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume3397
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event13th International Conference on AIS 2004 - Jeju Island, Korea, Republic of
Duration: 2004 Oct 42004 Oct 6

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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